Senior Engineers Lack AI Production Experience, So He Open-Sourced an Interview Prep Repo
jgarg27 · reddit · 2026-09-14
A startup engineer noticed a gap while helping his wife (a big-tech senior backend engineer) prep for interviews: large orgs specialize, so even strong senior engineers can go years without touching LLM-serving or agent infrastructure, and most system design prep still teaches the pre-2024 interview — missing explicit grading on cost/failure-mode reasoning and mainstream questions like "design an LLM serving system."
He open-sourced a focused repo with:
- 8 "AI Production Systems" prompts (RAG, LLM serving infra, agent guardrails, observability, eval pipelines) explaining mechanisms, not buzzwords
- 15 classical distributed systems prompts as a lighter companion
- Every claim sourced to primary docs: Orca and vLLM papers, DistServe, Anthropic's agent writeup, OpenTelemetry GenAI conventions, OpenAI evals docs
Drafted with Claude's help, but all technical claims verified against primary sources with inline links.
More from coding & agent
- 5 specialized inference engines in a month: why fork the ecosystem when vLLM/SGLang can hit near-SOL? — hsu_byron · 2026-09-14
- iOS AI dev workflow: AppKit + Figma import + Claude Opus 5 gives best UI fidelity — dotey · 2026-09-14
- Dev seeks blueprint for agent that triages incidents across PagerDuty, Datadog, GitLab and Slack — cruelcaricature · 2026-09-14
- Redpen CLI checks whether your coding agent's 'done' claim matches repo, test and build evidence — Scobleizer · 2026-09-14
- Infinite Bookshelf: open-source app generates a whole book from one prompt using Llama on Groq — Roger_M_Taylor · 2026-09-14
- Agent Harness explained: freeCodeCamp compares 10 tools from Claude Code to DeepSeek Harness — Roger_M_Taylor · 2026-09-14